Abnormal or diseased biological tissues are often diagnosed and monitored with histopathology. For example, a majority of cancer cases are diagnosed by histopathological assessment of a biopsy sample. The presence, concentration and distribution of biological molecules (such as nucleic acid, protein or lipids for example) or different portions and structures of the tissue can be determined by selecting a specific combination of chemical stains and fixatives. Visualization of the histological structures in a biological tissue sample is a basic procedure undertaken by a pathologist to reach a specific diagnosis on the disease that might have afflicted a patient, for example, kidney disease, liver disease, and the like. In particular, a pathologist assesses any variation in the morphological structures of the different components of the tissue, such as irregularities in shapes and sizes, and correlates the identified changes, if any, to a particular disease. Normally, a pathologist uses a physically stained tissue sample (a sample stained with a dye, for example) and relies on color cues to interpret texture and morphology of such tissue in arriving at his diagnosis. In comparison with an unstained tissue sample, in which histological structures are not clearly differentiated, and which generally appears colorless when viewed under a microscope, a stained tissue specimen provides a clear illustration of the histological structures as well as vivid visual discrimination of the different tissue components. Various types of dyes are available to stain the tissue samples, each of the dyes labeling the histological structures with distinguishing colors, thereby emphasizing the differences among such components. Choice of which type of stain to use depends on mainly on what tissue structure is to be assessed in the diagnosis. Popular for routine staining are, for example, the Hematoxylin and Eosin (H&E) dyes that facilitate differentiation between the nuclear region and the cytoplasm and connective tissues. A well-trained histopathologist can diagnose and grade the severity of a tissue disease based on colour, shape, degree of staining and pattern of a variety of stains.
More recently, digital technology has been developed to digitally “stain” images. Digital staining of an image is understood as the process of digitally converting the original image into an image with visual characteristics mimicking those that would be observed if the tissue were to be conventionally stained. As is the case with many traditional clinical applications being advanced with digital technology, the advantages of digital staining are multifold. For example, digital staining provides a quantitative result, which could aid diagnosis and reduce the hands-on time of a trained histopathologist as well as reduce intra-histologist variation in diagnosis. It offers the opportunity to develop a variety of digital staining procedures and has the potential to be significantly cheaper than existing chemical staining techniques. Moreover, digital staining does not destroy the biological sample and therefore the same sample could be analyzed by multiple digital staining protocols. Finally, the digital staining process does not involve toxic chemical stains, and is, therefore, intrinsically harmless to the user.
Of course, in the sense that implementations of digital staining are designed to mimic or reflect visual characteristics provided to the clinician when performing traditional staining, the clinical utility and, ultimately, clinical acceptance of digital staining systems and methods are predicated on the accuracy of this mimicking of traditional staining visualizations. For example, one method of digital image staining relies on spectral classification of tissues and often cannot delineate portions of a given image representing tissues with similar spectral attributes. In particular, the reliable quantitative differentiation between those components of unstained tissue that have similar spectral response to a conventional physical staining (referred to herein as colorimetrically-similar components) cannot be assured with the use of conventional digital staining. Thus, the field of digital staining continues to develop with the goal of improving clinical feasibility of such digital staining techniques.
It is desired, therefore, to provide apparatus and method capable of improving the accuracy of digital staining techniques in reflecting traditional staining results, such as, for example, by resolving similarities is spectral response and appropriately enhancing histopathological images produced through digital staining for visualization by the user.